NDLI: Towards a platform-independent cooperative human-robot interaction system: I. Perception

Content Provider	IEEE Xplore Digital Library
Author	Lallée, S. Lemaignan, S. Lenz, A. Melhuish, C. Natale, L. Skachek, S. van Der Zant, T. Warneken, F. Dominey, P.F.
Copyright Year	2010
Description	Author affiliation: IIT, Genoa, Italy (Natale, L.) \|\| LAAS, CNRS, Toulouse, France (Lemaignan, S.) \|\| Harvard University, Cambridge, USA (Warneken, F.) \|\| BRL, Bristol, United Kingdoms (Lenz, A.; Melhuish, C.; Skachek, S.) \|\| Stem Cell & Brain Research Institute, INSERM U846, Bron, France (Lallée, S.; van Der Zant, T.; Dominey, P.F.)
Abstract	One of the long term objectives of robotics and artificial cognitive systems is that robots will increasingly be capable of interacting in a cooperative and adaptive manner with their human counterparts in open-ended tasks that can change in real-time. In such situations, an important aspect of the robot behavior will be the ability to acquire new knowledge of the cooperative tasks by observing humans. At least two significant challenges can be identified in this context. The first challenge concerns development of methods to allow the characterization of human actions such that robotic systems can observe and learn new actions, and more complex behaviors made up of those actions. The second challenge is associated with the immense heterogeneity and diversity of robots and their perceptual and motor systems. The associated question is whether the identified methods for action perception can be generalized across the different perceptual systems inherent to distinct robot platforms. The current research addresses these two challenges. We present results from a cooperative human-robot interaction system that has been specifically developed for portability between different humanoid platforms. Within this architecture, the physical details of the perceptual system (e.g. video camera vs IR video with reflecting markers) are encapsulated at the lowest level. Actions are then automatically characterized in terms of perceptual primitives related to motion, contact and visibility. The resulting system is demonstrated to perform robust object and action learning and recognition on two distinct robotic platforms. Perhaps most interestingly, we demonstrate that knowledge acquired about action recognition with one robot can be directly imported and successfully used on a second distinct robot platform for action recognition. This will have interesting implications for the accumulation of shared knowledge between distinct heterogeneous robotic systems.
Starting Page	4444
Ending Page	4451
File Size	922893
Page Count	8
File Format	PDF
ISBN	9781424466740
ISSN	21530866
e-ISBN	9781424466764
DOI	10.1109/IROS.2010.5652697
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot kinematics Computer architecture Humans Robot sensing systems Ontologies Context
Content Type	Text
Resource Type	Article

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